This section is intended to provide a background or context to the invention that is, inter alia, recited in the claims. The description herein may include concepts that could be pursued, but are not necessarily ones that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, what is described in this section is not prior art to the description and claims in this application and is not admitted to be prior art by inclusion in this section.
The present invention relates generally to the field of systems and methods for automatically building a model to evaluate an automotive propulsion system and/or subsystems. More specifically the present invention relates to methods and systems for automating the design, analysis, and development of an automotive propulsion system and/or subsystem.
With the introduction of advanced propulsion technologies, including hybrid electric vehicles, fuel cells, etc, designers often must evaluate hundreds of vehicle propulsion system configurations for potential selection for a new or modified vehicle. Various configurations for evaluation may comprise, for example, a variety of powertrain types (conventional, electric, series, parallel, power split, etc), a multitude of component technologies (various types of transmission, engine, electric machines, battery, etc.), model complexity (steady-state, transients, etc.), and system controllers. Additionally, vehicles can be two or four wheel drive and have a variety of differentials, all of which may affect the performance of the vehicle. Still further, a model may consider various driving variables (steady-state conditions, transient effects such as acceleration and braking, grades, city/highway driving, etc.). These variables, plus others known in the art, but not mentioned here, can make up hundreds of configurations that must be taken into consideration when evaluating a vehicle propulsion system to arrive at an optimized system and/or system subcomponents for a particular vehicle design.
It is impracticable to build and evaluate a physical embodiment of every potential configuration and inefficient to do so for even a reasonable number of configurations. Accordingly, simulation may be used to develop and evaluate a large number of configurations relatively quickly and inexpensively. The benefits of modeling and simulation in allowing companies to accelerate the introduction of technology into the market have grown rapidly. With time, however, the size and complexity of simulation models have also increased, detracting from their efficiency.
In the transportation field, two principal techniques for simulating various powertrain configurations have been developed: (1) build all the simulation configurations by hand, and (2) modify a preexisting configuration. The first technique is used by conventional simulation applications such as AVL CRUISE and GT-DRIVE. Here, every model must be manually created by moving individual component models, for example, an engine, a clutch, and a fuel cell, from a library of component models into the simulation environment and then linking every component. The second is used in some other conventional simulation applications such as ADVISOR from AVL. However, in light of the vast number of potential combinations and complexity of such models, this technique is inefficient from both a modeling and data management perspective. Further, the number of permissible combinations that can be saved may be limited to an insufficient number. In either case, conventional simulation processes may take too long and have limited effectiveness and/or efficiency. In particular, development of a powertrain model for a vehicle may take several days to build and modifying such models requires additional time, all of which may more effectively be applied to running simulations on various configurations and analyzing the results of those simulations.